Techniques to Identify Operational Risks in Banks & FIs

Let’s look at some techniques banks or FIs can utilise in order to Identify operational risks.  

Process Deep-dives - A bank's operations extend beyond its core functions and encompass various teams. Many countries mandate that banks disclose the compensation of senior staff members and impose caps on such compensation (requiring approvals). While this falls under the HR function, it becomes an operational risk because a regulatory breach, even on HR matters, can disrupt operations. Consequently, divisional managers are required to define, own, and regularly audit their processes to identify any gaps or vulnerabilities. This process helps unearth new risks and endorse previously identified ones

Reporting & Data Analysis: Banks are required to regularly report to the regulators multiple data points . While this data is used for reg reporting its also has a key function of identifying risks within its operations. Hence reports and data generated from reports for analysis acts as basis for identifying risks within its operations  Banks don't wait for disaster to strike. By examining past internal data on financial losses, data breaches, compliance violations, and operational disruptions, they can identify trends and areas where issues frequently arise. This historical data provides valuable insights into potential future risks.

Scenario Analysis: Similar to broader risk assessment, banks think ahead by brainstorming potential scenarios that could disrupt operations. This might involve considering a cyberattack, a natural disaster, or even human error leading to a system failure. Analyzing these scenarios helps banks pinpoint areas where controls might be lacking.

Key Risk Indicators (KRIs) aka KPIs: For a manager in a banking entity the KRI is their KPI. Once potential risks are identified, banks establish KRIs to monitor them. KRIs are metrics designed to serve as early warning signs of potential operational risk events. By tracking these indicators, banks can take preventive actions before problems escalate.

Combining these methods provides a comprehensive approach to operational risk identification. For instance, process analysis might reveal a vulnerability in a loan approval process. Examining past loss data (loss from fraudulent loans) would confirm the risk, and scenario analysis could explore potential consequences of such fraud. Finally, KRIs could be established to track suspicious loan applications.